Reference: EXM-MS-TNO-LMD-0034
Date: 14/may/2011
Issue: 01
Page: 1/23
Exomars Environmental Atmospheric Support Analysis
Phase B2X2
Contract EXM-SC-LMD-0969 deliverable: WP6
Thermosphere variability and applicability of the Mars
Climate Database to aerobraking
Prepared by François Forget
Laboratoire de Météorologie Dynamique,
Université Pierre et Marie Curie, Paris, France
Contact: [email protected]
May 14, 2011
Table of contents
1 Background: Modelling physical processes in the Mars upper atmosphere and
thermosphere. ............................................................................................................................. 3 1.1 Mars upper atmosphere processes ............................................................................... 3 1.2 Modelling the upper atmosphere with the LMD General Circulation Model. ............ 4 2 Sources of atmospheric variability at the aerobraking altitude range ............................... 5 2.1 Available data .............................................................................................................. 5 2.1.1 Accelerometer measurements during previous aerobraking campaigns. ............. 5 2.1.2 Stellar occultations using the UV spectrometer SPICAM. .................................. 5 2.2 Dust variations and dust storms in the lower atmosphere. .......................................... 7 2.2.1 Seasonal variations. .............................................................................................. 7 2.2.2 Short term variations ............................................................................................ 8 2.3 Solar Extreme Ultraviolet (EUV) variability............................................................... 9 2.4 Variability due to atmospheric waves ....................................................................... 10 2.4.1 Travelling planetary waves ................................................................................ 10 2.4.2 Thermal tides. ..................................................................................................... 10 2.4.3 Small scale waves............................................................................................... 11 3 Applicability of the Mars Climate Database V4.3 ........................................................... 12 3.1 Prediction of the absolute density. Comparison with SPICAM data. ....................... 12 3.2 Prediction of the absolute density and travelling wave variability. Comparison with
Mars Odyssey accelerometer data. ....................................................................................... 18 3.3 Prediction of the variability induced by thermal tides. Comparison with Mars Global
Surveyor data........................................................................................................................ 18 3.4 Prediction of small scale gravity waves. ................................................................... 19 3.5 Upcoming improvements of the Mars Climate Database for the prediction of the
atmospheric environment at aerobraking altitudes............................................................... 20 4 References ........................................................................................................................ 21 1
1.1
Background: Modelling physical processes in the Mars upper
atmosphere and thermosphere.
Mars upper atmosphere processes
In the Mars lower atmosphere (below 50 km), the thermal structure is mostly controlled by
the interaction of the solar and infared radiations with the airborne dust and ice particles, and
the absorption of thermal infrared absorption by the CO2 gas 15 µm band (and by the
resulting dynamical heating and cooling).
In the aerobraking range of altitude (90-150 km), other processes must be taken into account
to understand and model the atmosphere and its variability (Figure 1).
Between 80 and 120 km:
 One must take into account the absorption of near infrared radiation by the CO2
gas. Above about 80 km, this absorption must be calculated taking into account
complex “Non Local Thermal equilibrium” (NLTE) processes. The main impact of
the NLTE is that a fraction of the energy absorbed is emitted back to space instead of
heating the gas as in LTE.
 Similarly, the thermal infrared absorption emission of CO2 becomes very complex
because of these NLTE processes which are sensitive to many parameters difficult to
compute. In particular, atomic oxygen collisions partly control this process. Such
collision are effective in exciting CO2 vibrational states, resulting in enhanced 15-μm
emissions and cooling.
Above the homopause, beyond 120 km (10-4 Pa pressure level), several additional processes
modify the physics of the atmosphere:
 The atmospheric gases, especially CO2, can absorb the Extreme ultraviolet radiation
which strongly heat the atmosphere and creates the thermosphere. The “EUV” flux is
much more variable than the total solar fluxes and fluctuates depending on the solar
activity. Thermospheric temperatures thus follow the 11-years solar cycle. Mars
dayside peak EUV heating rates occur at ~150-170 km
 At such low pressure, the mean free path of the molecules is relatively large and the
Molecular thermal conduction redistributes heat opposite to the temperature
gradient. Typically, EUV heat deposited above ~130 km is conducted downward
toward the mesopause (~90-110 km) where CO2 15-μm emission radiates this heat to
space
 The thermosphere is also distinguished by this transition region called the homopause
(~115-130 km), below which atomic and molecular constituents are well mixed.
Above, in the heterosphere, individual species separate according to their unique
scale heights via molecular diffusion. Mars’ thermosphere is dominated by CO2 and
its dissociation products O and CO, as well as N2.
 Locally, temperature and density will also be controlled by adiabatic heating and
cooling associated with global dynamics.
Figure 1. The mean radiative heating and cooling rates of the Mars upper atmosphere.
1.2
Modelling the upper atmosphere with the LMD General Circulation Model.
The LMD General Circulation Model has been extended into the thermosphere by including
the processes listed above in the physics of the model in collaboration with the Instituto de
Astrofısica de Andalucıa (IAA) based in Granada, Spain (The dynamical core is thought to be
valid in the thermosphere up to the exobase above 200 km).
This was the first single Martian GCM able to self-consistently study the whole atmospheric
range from the surface up to the upper thermosphere. This allows the model to selfconsistently study the coupling between the lower and the upper atmosphere, essential for the
determination of the structure of the upper atmosphere.
The up-to-date details of the model are documented in the paper by Gonzalez-Galindo et al.
(2009a). Other references are in earlier publications by Angelats I Coll (2005), GonzalezGalindo et al. (2005) and a companion paper by Gonzalez-Galindo et al. (2010).
In summary, fifty vertical levels are used, with an uneven sampling to allow for a higher
vertical resolution close to the surface, giving a vertical resolution of about 7 km in the
thermosphere. It uses a hybrid coordinate system, with sigma coordinates in the lower
atmosphere and pressure coordinates in the upper layer. Horizontally, it was run with a 64 ×
48 longitude-latitude grid for the Mars Climate Database.
To simulate the upper atmosphere, the LMD-MGCM includes a parameterization of the IR
radiative transfer under NLTE conditions, based on López-Valverde and López-Puertas
(2001) and López-Valverde et al. (1998), a fast scheme to calculate the UV heating, a
photochemical model especially developed for the study of the rarified Martian upper
atmosphere (González-Galindo et al., 2005), which considers the chemistry of the C, O, H,
and N families and ionospheric reactions, and schemes for the molecular diffusion and
viscosity.
The model has been used for comparisons with data such as the longitudinal variations of
thermospheric densities obtained during MGS aerobraking (Angelats i Coll et al., 2004), the
thermospheric polar warming observed during Mars Odyssey aerobraking (González-Galindo
et al., 2009b), the NO nightglow observed by SPICAM (González-Galindo et al.,2008), the
thermospheric densities derived from MGS electron reflectrometry (Lillis et al., 2010) and the
SPICAM temperature and density profiles (Forget et al., 2009), have validated the model and
identified areas of needed improvement (see below).
The LMD GCM is not the only GCM simulating the thermosphere. In particular, the reference
model used by NASA (to derive Mars–Gram and and prepare aerobraking campaigns) is the
The Mars Thermospheric General Circulation Model (MTGCM) now developed at the
University of Mishigan (e.g., Bougher et al., 1990). The LMD GCM has recently been
compared to the MTGCM, showing that both models predict similar thermospheric
temperatures when similar inputs are used (González-Galindo et al., 2010).
2
Sources of atmospheric variability at the aerobraking altitude range
What are the sources of variations of density in the Martian upper atmosphere which can
impact aerobraking campaigns and in particular induce orbit to orbit density variations? In
addition to the expected smooth evolution with season and latitude, we shall focus on 1) Dust
storms in the lower atmosphere, 2) Solar EUV variability 3) Atmospheric waves.
2.1
Available data
There are two main sources of measurements available on the density of the atmosphere at
aerobraking altitudes:
2.1.1 Accelerometer measurements during previous aerobraking campaigns.
Accelerometers onboard aerobraking spacecrafts allowed to retrieve atmospheric density
profile. Three spacecraft missions have provided such data:
 Mars Global surveyor (MGS): the aerobraking campaign began in September 1997
and ended with over 850 passes (Keating et al. 1998, Withers 2006).
 Mars Odyssey (ODY) followed in October 2001 with over 300 passes (Withers 2006).
 Mars Reconnaissance Orbiter (MRO) began aerobraking in April 2006 and ended in
August 2006 with 425 passes (Keating 2007, Tolson et al. 2008).
All of these Mars missions established sun synchronous orbits for the science phase with 93deg inclinations. The spacecraft were equipped with three axis accelerometers with
measurement noise below 0:5 mm=s for a 1-s count and allowed density recovery to better
than 1 kg/km3. As seen in Figure 2, periapsis locations for these missions cover a significant
fraction of the seasonal (Ls), diurnal (LST), and latitudinal space of interest for validation of
atmospheric models.
2.1.2 Stellar occultations using the UV spectrometer SPICAM.
By observing the setting or the rising of selected stars through the atmosphere from the Mars
Express spacecraft, it has been possible to retrieve the density of CO2 from about 70 km to
above 130 km. Forget et al. (2009) reported on the analysis of 616 profiles between March
2004 and February 2006 (Martian year 27). Figure 4 shows the distribution of these profiles.
Figure 2. The distribution of available aerobraking data from Mars Global Surveyor, Mars Odyssey,
Mars Reconnaissance Orbiter (Tolson et al. 2007)
.
Figure 3. The distribution of available aerobraking density measurements from Mars Global Surveyor,
Mars Odyssey, Mars Reconnaissance Orbiter.
Figure 4. The spatial and seasonal distribution of the 616 available SPICAM stellar occultations . (a)
Locations of the occultations superimposed on a topography map of Mars. (b) The latitudinal
distribution of the occultations as a function of season. The black solid line shows the latitude of the
subsolar point. Shaded areas illustrate the extension of the polar nights. (Forget et al. 2009)
2.2
Dust variations and dust storms in the lower atmosphere.
The presence of dust in the Martian atmosphere between the surface and up to 80 km warms
the atmosphere and thus strongly influences the density at aerobraking altitudes.
Indeed, the density ρ at a given altitude z is proportional to pressure p (ρ = p/RT, with
R = 192 m-2 s-2 K-1 the gas constant and T the temperature). Pressure primarily depends on the
mean scale height H of the atmosphere below this level (roughly, p = p0e-z/H, with p0 pressure
at z = 0 km). H is proportional to the mean temperature T (H = RT/g with g = 3:72 m s-2 the
acceleration of gravity).
2.2.1 Seasonal variations.
Available data (MGS/TES, MRO/MCS) shows that, during years without global dust storms,
the tropical and mid-latitude atmospheric temperature from a few kilometers above the
surface up to at least 50 km typically fluctuates with a total amplitude of about 20 to 40 K
between a minimum near Ls = 70-90° and a maximum around Ls= 250°. This, combined with
the variations of the solar fluxes on the eccentric Mars orbit creates large seasonal variations.
This was well quantified in SPICAM observations. For instance Figure 5a shows the
variations of the CO2 density at 100 km with season during Martian Year 27 for latitude
between 50°S and 50°N. The correlation with atmospheric dust opacity can be observed by
comparing Figure 5a and 5b.
Figure 5 (a). CO2 density measured by SPICAM as a function of season at various altitudes above the
Mars zero datum (areoid). Only the data obtained below 50° latitude are shown (Forget et al. 2009) (b)
Dust optical depth at 1075 cm-1 (9.3 µm) as function of season for the Mars Exploration Rovers Spirit
(top) as retrieved by Smith et al. [2006] using Mini-TES spectrometer observations. The data were
obtained during the same year than the SPICAM data above. The fluctuations of atmospheric dust
optical depth appear to be correlated with the density variations in the upper atmosphere observed by
SPICAM.
2.2.2 Short term variations
Similarly, intense local or regional storms can have a strong impact on density at aerobraking
altitudes. Because such storms can develop in less than a few days, they can be a concern
during aerobraking campaigns. This was for instance the case during the phase 1 of Mars
Global Surveyor aerobraking campaign. Figure 6 shows the density variations as measured by
the MGS spacecraft at that time.
Figure 6 Response of density at 140 km to a regional dust storm in Noachis for both inbound (upper)
and outbound (lower) legs. MGS started aerobraking again on orbit 40. Thirteen orbits later, the
Noachis regional dust storm occurred and the density at periapsis increased by more than 100%. Over
the rest of MGS phase 1, the density seemed to exponentially decay back to expected values. A model
was fit to these data that assumed density varied quadratically with latitude over the entire data set and
exponentially with time after orbit 52. (Tolson et al. 2007)
2.3
Solar Extreme Ultraviolet (EUV) variability
As mentioned above, above 120 km the thermosphere is directly heated by the EUV solar
flux. This induces large variations in the temperature (Figure 7a). To describe the solar
conditions and the expected EUV fluxes, scientists usually employ the F10.7 index which is
easy to monitor from the Earth and which is a measure of the noise level generated by the Sun
at a wavelength of 10.7 cm at the earth's orbit. F10.7 is assumed to be a proxy for solar EUV
irradiance. Figure 7b illustrates the large interranual variations and the possible short term
variations induced by the solar activity.
Altitude
(km)
Temperature (K)
Figure 7. Left: Impact of the variations of the solar flux on the temperature profiles predicted by the
Mars Climate database at at 0°N. Right: variations of the solar F10.7 index which is used as a proxy
for the solar EUV flux.
2.4
Variability due to atmospheric waves
The Martian atmosphere is a medium through which various kinds of waves can propagate.
Waves resulting from a forcing near the surface tend to propagate upward and to conserve
their energy. Because the density decreases, to first order the amplitude of the waves also
increase in the vertical, and the role of the waves in the upper atmosphere and in particular at
aerobraking levels can be strong;
2.4.1 Travelling planetary waves
Travelling waves are planetary waves with typically a period of several days. In the lower
atmosphere they are usually associated to baroclinic instabilities (the meteorological process
that form the low and high pressure systems at mid-latitudes on the Earth). Such waves can
propagate upward, especially in regions with westerly (prograde) jets. At high altitude,
modeling suggests that other kind of waves can be present (Figure 8)
2.4.2 Thermal tides.
Thermal tides are planetary waves that results from the diurnal heating of the sun at the
surface and in the lower atmosphere [Zurek et al. 1992, Wilson and Hamilton 1996]. In
addition, in the upper atmosphere,direct CO2 heating in the near infrared and EUV heating
can play a role. They are a major component of Mars atmosphere dynamics. They propagate
upward with a growing amplitude as the density decrease.
 Westward sun-synchronous waves: The dominant mode is usually the westward
diurnal tide (like the sun) with a period equal to the length of the Martian day and an
horizontal wavelength equal to the circumference of Mars. The typical vertical
wavelength is of the order of 20 to 30 km. Another mode is the semidiurnal tide (with
period equal to one-half Martian day and wavelength equal to half the planetary
circumference), with a much larger theoretical vertical wavelengths around 100 km. In
practice, the impact of the sun-synchronous waves on the density variations
encountered by aerobraking spacecrafts has been small because these spacecrafts were
close to sun-synchronous orbit so that the sampled local time was constant or slowly
moving. With a spacecraft with an inclination near 74°, the signature of such waves
should be a slow variation of the density evolving with the local time at periapsis. .
 Eastward “non-migrating tides”: The interaction of the solar forcing with
topography induces multiple harmonics (e.g. Kelvin waves) which can reach a
significant amplitude, especially in the equatorial regions. Some of these harmonics
correspond to waves with diurnal or simi-diurnal frequencies and various
wavenumbers which can propagate in the opposite direction than the solar forcing, i.e.
eastward. These features appear as stationary waves from an orbit that processes
slowly in local time In other words, at fixed local time density appears to vary with
longitude (Figure 9). Because the longitude of the pariapsis strongly varies from one
orbit to the next, these waves are the main source of orbit-to-orbit variations
experienced by aerobraking spacecrafts, at least at low to mi latitudes.
2.4.3 Small scale waves
Accelerometer measurements have provided evidence of significant small scale wave
structures encountered by the aerobraking spacecrafts. This is illustrated on figure 10 which
shows a measurement by Mars Odyssey exhibiting strong waves structures. Such
perturbations probably results from small scale gravity waves propagating to aerobraking
altitudes.
Figure 8. Variation in the dynamical fields of the Martian atmosphere as simulated by the LMD
General Circulation Model (Forget et al., 1999) during Northern winter: temperature T, zonal wind U
(eastward) and meridional wind V (northward). The middle and right columns shows the expected
RMS amplitude of key meteorological phenomena thought to create day to day variability (transient
waves) and diurnal oscillations (thermal tides).
z=120 km
z=130 km
z=140 km
z=150 km
z=160 km
Figure 9. Variations of density a measured by Mars Global Surveyor between orbit 527 and 626
(crosses). Most of the variability result from longitudinal variations resulting from “non-migrating”
thermal tide waves.
Figure 10. Accelerometer measurements of the atmospheric density obtained during one aerobraking
pass by Mars Odyssey during orbit 199 (Ls=302°, periapsis at 72°N). This profile is characterized by
particularly strong small scale waves signature, but such waves are not uncommon in the aerobraking
data.
3
3.1
Applicability of the Mars Climate Database V4.3
Prediction of the absolute density. Comparison with SPICAM data.
The Mars Climate database density predictions have been compared to the available
measurements of density at aerobraking altitudes.
Figure 11 shows a comparison of SPICAM observations plotted as a function of season (as in
Figure 5a) with predictions from the Mars Climate Database at the same location and time
(with no variability included: the effect of thermal tides is included but the transient day-today variability is completely smoothed out). To first order, the MCD densities roughly follow
the observed seasonal evolution. The observations are more scattered than the modeled
values, probably because of transient waves. The model underestimates densities between
Ls=140° and Ls=180°, certainly because of the unusual dust loading observed in Martian year
27 (2004) and not present in the Martian Year 24 (2000-2001) dust scenario used to force the
GCM simulations used in the database. However, outside this period, the predicted densities
are in most case higher than observed. The discrepancy is significant at 70 km, and increases
at higher altitude.
By examining the available TES data, Forget et al. (2009) showed that this difference is
probably not due to a lower atmosphere less dusty and less warm on MY 27 compared to
MY24. Morever, it was found that the overestimation of density by the model cannot even be
copped by assuming a very clear atmosphere like in the MCD “clear” scenario (Figure 12).
One possibility is that the middle atmosphere between 10 Pa and 0.1 Pa (i.e. between 40 and
70 km) was colder than predicted by the MCD. Using the hydrostatic equation, one can show
that the 30% density difference observed at 70 km on Figure 11 would be explained by a 10 K
temperature difference between 40 and 70 km.
Latitudinal variations of density can also be detected by SPICAM and compared to MCD
predictions. The observed density at 100 km for the periods Ls=30-120°, Ls=130-180° and
Ls=240-300° are plotted as a function of latitude in Figure 14. The density measured around
southern winter solstice (Ls=30-120°) decreases by about one order of magnitude between the
tropics and the polar night, certainly because of the decrease of temperature in the atmosphere
below. This is correctly predicted by the MCD. At other seasons, no clear structure can be
identified (unfortunately no SPICAM data are available in the northern winter polar night).
Nevertheless, the MCD does a reasonable job to predict the spread and the possible variations
seen in the observations. One exception is the northern winter mid-latitudes around Ls=240300°: Above 30°N, the GCM often overestimates the density.
The overestimation of the observed densities by the MCD strongly increases with altitude.
This suggests that the modeled scale heights of the atmosphere are generally larger than in
reality, and that the MCD temperatures above 70 km are overestimated. This is illustrated in
Figure 14 which shows a selection of 12 averaged profiles representing all the latitudes and
seasons observed by SPICAM, compared to MCD predictions obtained with our various dust
and solar EUV scenarios. In many cases, the MCD strongly overestimates the observed
temperatures around 0.001 Pa (85-100 km). The shape of the temperature profiles suggests
that the differences result from the fact that 1) Mesopause temperatures are overestimated by
the model. and 2) Mesopause altitudes tend to be underestimated by the model.
Our analysis suggests that this discrepancy probably results from errors in the modeling of the
radiative transfer processes and in particular in the estimation of the CO2 thermal infrared
cooling (Forget et al. 2009).
Figure 11. Comparison of SPICAM observations plotted as a function of season as in Figure 4 with
MCD predictions at the same location and time (MCD data are from our .refererence MY24 scenario).
Except during the unexpected dusty period between Ls=140° and Ls=180°, the MCD tends to
overestimate the density observed by SPICAM
Figure 12. Same as Figure 11 for altitudes 70 and 100 km above areoid and with MCD predictions
obtained with the three dust scenarios in the Mars Climate database version 4.3 : MY24 scenario
(green), warm scenario (red), cold scenario (blue).
Figure 13. Comparison of SPICAM density at 100 km plotted as a function of latitude with MCD
predictions at the same location and time. Three seasons are shown. MCD data are from the reference
MY24 dust scenario (Forget et al. 2009).
Figure 14. Average SPICAM temperature profiles as a function of pressure for selected season and
latitudinal range, compared to MCD temperature profiles obtained at exactly the same location and
time and similarly averaged. In each cases, three mean SPICAM profiles obtained assuming top
temperatures of 100, 175 and 250 K. are shown. The three MCD profiles correspond to the MCD
scenarios “MY24” (green), “cold” (blue) and “warm” (red). Forget et al. 2009.
3.2
Prediction of the absolute density and travelling wave variability. Comparison
with Mars Odyssey accelerometer data.
Figure 15 shows comparisons of all Mars Odyssey aerobraking density measurements at 120 km
with predictions from the Mars Climate Database V4.3 at the same location and time. It confirms the
fact that the Mars Climate Database tends to globally overestimate density. With regard to variability,
the dispersion of the data is clearly larger in the data than in the MCD outputs when no additional
perturbation is added. However, adding large scale perturbations (day to day variability created by
travelling waves in the GCM) and small scale perturbations (gravity waves) as provided by the Mars
Climate database spread the measurements in a manner comparable to the observations.
Figure 15. Comparison of all Mars Odyssey aerobraking density measurements at 120 km with
predictions from the Mars Climate Database V4.3. Top: average MCD data. Bottom: MCD v4.3data
including large scale and small scale perturbations.
3.3
Prediction of the variability induced by thermal tides. Comparison with Mars
Global Surveyor data.
The signature of non-migrating tides (which creates large orbit to orbit variations) observed
by Mars Global Surveyor were analysed in details with the previous version of the database
(Version 3) by Angelats I Coll et al. (2004)
[http://wwwmars.lmd.jussieu.fr/mars/publi/angelats_jgr2004.pdf].
It was found that in most cases the MCD was able to predict with accuracy the structures of
the waves, which often combine various harmonics in a very complex way. Figure 16 shows a
similar comparison performed for a subset of the MGS data (crosses), but using the current
Mars Climate version 4.3 (squares). At 130 and 140 km the MCD predicts rather well the
density, but it is clear that the model overestimates the density at 150 and 160 km, as
explained above. The observed density shows a wave-3 longitudinal structure, that is very
well reproduced by the model, with minimum and maximum densities at the same longitudes
than where they have been observed.
Figure 16. Atmospheric density at 130, 140, 150 and 160 km altitude, as a function of longitude,
measured during MGS aerobraking (crosses) and simulated by the model (squares). Courtesy of
F. Gonzalez-Galindo and M Lopez-Valverde.
3.4
Prediction of small scale gravity waves.
Figure 17 shows a comparison of the density measurements obtained by Mars Odyssey during
one aerobraking pass (previously shown in figure 10) with prediction from the Mars climate
database with various “seeds” for the small scale perturbation tool included in the MCD
software. If we allow the random seeding of the perturbation at every data points or every 10
seconds, the amplitude of the perturbation appears to be in agreement with the observations
(Figure 17). However, it is clear that the tool is not adapted to simulate such trajectories. The
MCD small scale perturbation tools was designed to simulate entry profile or observed
temperature vertical profile perturbed by a gravity waves propagating from below. It does not
include a representation of the horizontal structure of the small scale waves which can be
detected during an aerobraking pass. In such a context, changing the seed can be a “poor
man” way of simulating the changes in density experienced by a spacecraft flying through the
thermosphere. Each time you use a new seed, it means that you simulate a new atmospheric
wave structure independent of the previous one. This can roughly represent the passage
through different wave structures.
Figure 17. Comparison of the Mars Climate database prediction with accelerometer measurements of
the atmospheric density obtained during one aerobraking pass by Mars Odyssey during orbit 199
(Ls=302°, periapsis at 72°N) with various kind of MCD perturbations and random seed.
3.5
Upcoming improvements of the Mars Climate Database for the prediction of the
atmospheric environment at aerobraking altitudes.
Thars Climate Database version 5 (currently in preparation with a target release date at the
end of 2011/early 2012) will be based on a new generation General Circulation Model that
will address many of the problems of MCD v4, described above
 The thermal structure in the lower atmosphere, and thus the absolute value of the
density in the lower thermosphere will be improved thanks to a new scheme used to
represent the dust radiative properties and vertical distribution, as well as clouds. It
will combined “dust scenarios” of different years. Finally it will benefit from the
tuning and the validation of the model with the Mars Climate data, available between
0 and 70-80 km altitude.
 In the upper atmosphere, thanks to the collaboration with F. Gonzalez-Galindo and
M. Lopez Valverde (IAA, spain), the GCM will include a new scheme for the thermal
cooling rates, which handles for the first time the actual atomic oxygen (the one
employed to create MCD v4 used a fixed prescribed profile of atomic oxygen), and
introduces a better treatment of radiative transfer in the 15-um bands (the previous one
used much more approximate methods). The solar heating rate model will also be
significantly revised and improved. Finally, the molecular diffusion scheme will be
updated, in order to improve the calculation of the mixing ratio of species like H or H2
above the homopause.
 The upper atmosphere model will be tuned and validated using all available data
(including observations of the ionosphere, CO2 clouds, ionospheric data, groundbased observations of mesospheric winds), with in particular SPICAM data and all
aerobraking accelerometer data
4
References
Angelats i Coll et al., 2004
Angelats i Coll, M., Forget, F., López-Valverde, M. A., Read, P. L., and Lewis, S. R. (2004).
Upper atmosphere of Mars up to 120 km: Mars Global Surveyor accelerometer data analysis
with the LMD general circulation model.
J. Geophys. Res., page 1011.
Angelats i Coll et al., 2005
Angelats i Coll, M., Forget, F., López-Valverde, M. A., and González-Galindo, F. (2005).
The first Mars thermospheric general circulation model: The Martian atmosphere from the
ground to 240 km.
Geophys. Res. Lett., 32:4201.
Bougher et al., 1990
Bougher, S. W., Roble, R. G., Ridley, E. C., and Dickinson, R. E. (1990).
The Mars thermosphere. II - General circulation with coupled dynamics and composition.
J. Geophys. Res., 95:14811-14827.
Forget et al., 1999
Forget, F., Hourdin, F., Fournier, R., Hourdin, C., Talagrand, O., Collins, M., Lewis, S. R.,
Read, P. L., and Huot., J.-P. (1999).
Improved general circulation models of the Martian atmosphere from the surface to above
80 km.
J. Geophys. Res., 104:24,155-24,176.
Forget et al., 2009
Forget, F., Montmessin, F., Bertaux, J.-L., González-Galindo, F., Lebonnois, S., Quémerais,
E., Reberac, A., Dimarellis, E., and López-Valverde, M. A. (2009).
Density and temperatures of the upper Martian atmosphere measured by stellar occultations
with Mars Express SPICAM.
Journal of Geophysical Research (Planets), 114(E13):1004-+.
González-Galindo et al., 2010
González-Galindo, F., Bougher, S. W., López-Valverde, M. A., Forget, F., and Murphy, J.
(2010).
Thermal and wind structure of the Martian thermosphere as given by two General Circulation
Models.
Planetary and Space Sciences, 58:1832-1849.
González-Galindo et al., 2009a
González-Galindo, F., Forget, F., López-Valverde, M. A., and Angelats i Coll, M. (2009a).
A Ground-to-Exosphere Martian General Circulation Model. 2. The Atmosphere During
Perihelion Conditions: Thermospheric Polar Warming .
Journal of Geophysical Research (Planets), in press.
González-Galindo et al., 2009b
González-Galindo, F., Forget, F., López-Valverde, M. A., Angelats i Coll, M., and Millour, E.
(2009b).
A Ground-to-Exosphere Martian General Circulation Model. 1. Seasonal, Diurnal and Solar
Cycle Variation of Thermospheric Temperatures.
Journal of Geophysical Research (Planets), in press.
González-Galindo et al., 2005
González-Galindo, F., López-Valverde, M. A., Angelats i Coll, M., and Forget, F. (2005).
Extension of a Martian general circulation model to thermospheric altitudes: UV heating and
photochemical models.
Journal of Geophysical Research (Planets), 110(E9):9008.
González-Galindo et al., 2011
González-Galindo, F., Määttänen, A., Forget, F., and Spiga, A. (2011).
The martian mesosphere as revealed by co2 clouds observations and general circulation
modeling.
Submitted to Icarus.
Keating et al., 2007
Keating, G. M., Bougher, S. W., Theriot, M. E., Tolson, R. H., Zurek, R. W., Blanchard,
R. C., Murphy, J. R., and Bertaux, J.-L. (2007).
Mars Neutral Upper Atmosphere Temporal and Spatial Variations Discovered from the
Accelerometer Science Experiment Aboard Mars Reconnaissance Orbiter.
In Lunar and Planetary Institute Conference Abstracts, volume 38 of Lunar and Planetary
Institute Conference Abstracts, pages 2074-+.
Keating et al., 1998
Keating, G. M., W., B. S., and 29-coauthors. (1998).
The structure of the upper atmosphere of mars: In situ accelerometer measurements from Mars
Global Surveyor.
Science, 279:1672-1676.
Lillis et al., 2010
Lillis, R. J., Bougher, S. W., González-Galindo, F., Forget, F., Smith, M. D., and Chamberlin,
P. C. (2010).
Four Martian years of nightside upper thermospheric mass densities derived from electron
reflectometry: Method extension and comparison with GCM simulations.
Journal of Geophysical Research (Planets), 115:E07014.
López-Valverde et al., 1998
López-Valverde, M. A., Edwards, D. P., López-Puertas, M., and Roldán, C. (1998).
Non-local thermodynamic equilibrium in general circulation models of the Martian
atmosphere 1. Effects of the local thermodynamic equilibrium approximation on thermal
cooling and solar heating.
J. Geophys. Res., 103:16799-16812.
Lopez-Valverde and Lopez-Puertas, 2001
Lopez-Valverde, M. A. and Lopez-Puertas, M. (2001).
Amospheric non-lte effects and their parameterization for mars.
ESA contract 11369 technical report.
Smith et al., 2006
Smith, M. D., Wolff, M. J., Spanovich, N., Ghosh, A., Banfield, D., Christensen, P. R.,
Landis, G. A., and Squyres, S. W. (2006).
One Martian year of atmospheric observations using MER Mini-TES.
Journal of Geophysical Research (Planets), 111(E10):12-+.
Tolson et al., 2008
Tolson, R., Bemis, E., Hough, S., Zaleski, K., Keating, G., Shidner, J., Brown, S., Brickler,
A., Scher, M., and Thomas, P. (2008).
Atmospheric Modeling Using Accelerometer Data During Mars Reconnaissance Orbiter
Aerobraking Operations.
Journal of Spacecraft and Rockets, 45:511-518.
Tolson et al., 2007
Tolson, R. H., Keating, G. M., Zurek, R. W., Bougher, S. W., Justus, C. G., and Fritts, D. C.
(2007).
Application of Accelerometer Data to Atmospheric Modeling During Mars Aerobraking
Operations.
Journal of Spacecraft and Rockets, 44:1172-1179.
Withers, 2006
Withers, P. (2006).
Mars Global Surveyor and Mars Odyssey Accelerometer observations of the Martian upper
atmosphere during aerobraking.
Geophys. Res. Letters, 33:2201-+.